About accuracy of the result about cfed-hanet HOT 8 CLOSED

Thank you for bringing this to my attention. Sorry for any inconvenience this discrepancy may have caused.
I've received the log file for the 'ACE/none/10class/5shot/shuffle_r1/perm0' experiment and will carefully review it.
I guess it might be caused by the hyperparameters. Given the current workload, I will check this before next Monday. Before that, can you provide detailed information on your GPU and CUDA Version? As I found that the GPU used and the cuda version may influence the experimental results greatly.
Thank you for your understanding.
Best regards!

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Thanks for your prompt reply! Below is the information regarding my PyTorch, GPU, and CUDA versions.
pytorch 2.2.1 py3.8_cuda12.1_cudnn8.9.2_0
NVIDIA GeForce RTX 4090 24GB
CUDA Version: 12.2

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And I've noticed another issue in the dataloader.py file within the utils directory: the (--my_test) argument has not been provided.

if args.my_test: return MAVEN_Dataset(data_tokens[:100], data_labels[:100], data_masks[:100], data_spans[:100]) # TODO:test use else: return MAVEN_Dataset(data_tokens, data_labels, data_masks, data_spans)

The comment in the code suggests # TODO:test use.
I used

return MAVEN_Dataset(data_tokens, data_labels, data_masks, data_spans)

for the three functions in the dataloader.py file, and I'm not sure if this is the reason why the F1 score has decreased.How should I use this parameter?

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The comment in the code suggests # TODO:test use.

It is not used for the test process, I actually use this for debugging.
Never use --my_test if you are not debugging, otherwise only 100 instances are used!
You can turn this off and evaluate again to see the results.
Besides, I will upload the full settings I used, you can check the updates in the last few days and compare the settings.
Best regards!

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Thank you! I'm looking forward to learning more about your full setting!

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Hi @Kohhh24, I've uploaded the necessary settings. If you have any other questions, feel free to contact us!

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I'm extremely grateful !

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Besides, if you find our work helpful, consider giving it a star!

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